Agent-Based Attribution Selection for Communicable Disease Surveillance Model Using Analytic Hierarchy Process

The Communicable diseases are becoming major issues in India due to economic, social and infrastructures. In particular, the statistics of 58% death in India between age group from 5 to 14 years are due to Communicable diseases. In Recently years almost all countries lost a considerable amount of their people due to the pandemic of COVID'19. A report of World Health Organization stated that, from 15th Feb'20 to 13th June'20 about 30,503,166 people were affected and 4,20,043(1% of total population) lost their lives. There are huge losses with respect economically and socially due to the recent communicable disease so called Covid'19, not just because it was new, but also because of failure to predict and manage the pandemic. This study proposes a design of an agent-based model for communicable diseases to effectively select primary symptoms of communicable diseases with its variants, since attributes selection is the core part of any analytics system. The consideration of all attributes can lead to waste of time, storage, and cost, as well as selection of inappropriate and inadequate attributes also leads to the results as inaccuracy. So, the proposed an agent -based model to select primary attributes of communicable diseases with any variants using Analytic Hierarchy Process, which will be used on collected data for prediction analysis instead of all attributes in the data set.